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Regression analysis for the determination of microplastics in sediments using differential scanning calorimetry
This research addresses the growing need for fast and cost-efficient methods for microplastic (MP) analysis. We present a thermo-analytical method...
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A semantic information-driven stepwise landslide displacement prediction model
Landslide prediction is critical for the early warning of a landslide occurrence. Existing stepwise landslide displacement prediction methods are...
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Multiple regression and group method of data handling-based models for predicting arsenic concentration in sedimentary phosphate rock
Marine sedimentary phosphate rock is the primary source for manufacturing phosphate fertilizers. It is composed mainly of phosphorus and other...
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Development and comparative analysis of ANN and SVR-based models with conventional regression models for predicting spray drift
As monitoring of spray drift during application can be expensive, time-consuming, and labor-intensive, drift predicting models may provide a...
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Assessment of dispersion of respirable particles emitted from opencast mining operations: development and validation of stepwise regression models
This study gives insight into the spatiotemporal variability of respirable PM concentrations around typically highly mechanized opencast coal mines...
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Trihalomethane prediction model for water supply system based on machine learning and Log-linear regression
Laboratory determination of trihalomethanes (THMs) is a very time-consuming task. Therefore, establishing a THMs model using easily obtainable water...
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Improved monthly streamflow prediction using integrated multivariate adaptive regression spline with K-means clustering: implementation of reanalyzed remote sensing data
This study investigates monthly streamflow modeling at Kale and Durucasu stations in the Black Sea Region of Turkey using remote sensing data. The...
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Effects of landscape structure on river water characteristics: a multi-scale analysis
This study aimed to assess the relationship between landscape characteristics and water quality in two distinct basins. Through the utilization of...
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Large Dataset-Based Regression Model of Chemical Toxicity to Vibrio fischeri
For the first time, a global regression quantitative structure–toxicity/activity relationship (QSTR/QSAR) model was developed for the toxicity of a...
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An eco-environmental efficiency analysis of Malaysia sewage treatment plants: an incorporated window-based data envelopment analysis and ordinary least square regression
Most human activities that use water produced sewage. As urbanization grows, the overall demand for water grows. Correspondingly, the amount of...
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Synergistic analysis of atmospheric pollutants NO2 and PM2.5 based on land use regression models: a case study of the Yangtze River Delta, China
Air pollution is considered one of the greatest threats to human health. This study combines a land use regression (LUR) model with satellite...
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Multimodel classification and regression technique for the statistical downscaling of temperature
Human activity has increased the amount of carbon dioxide and other greenhouse gases emitted into the atmosphere, causing climate change. As a...
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Evaluation of water quality based on artificial intelligence: performance of multilayer perceptron neural networks and multiple linear regression versus water quality indexes
A significant problem in the sustainable management of water resources is the lack of funding and long-term monitoring. Today, this problem has been...
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Regression based prediction of higher heating value for refuse-derived fuel using convolutional neural networks predicted elemental data and spectrographic measurements
Higher heating value (HHV) is the key parameter for replacing Refuse-Derived Fuel (RDF) with fossil fuels in the cement industry. HHV can be measured...
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Prediction of water quality extremes with composite quantile regression neural network
Water quality extremes, which water quality models often struggle to predict, are a grave concern to water supply facilities. Most existing water...
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Stream water quality prediction using boosted regression tree and random forest models
Reliable water quality prediction can improve environmental flow monitoring and the sustainability of the stream ecosystem. In this study, we...
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Stepwise aggregation method for the WQI-CCME to generate a water quality profile for a long river: case study—São Francisco River, Brazil
This paper presents a new aggregation method to calculate the WQI-CCME, named stepwise aggregation method, to communicate the water quality of the...
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Analysis of spatial distribution characteristics and main influencing factors of heavy metals in road dust of Tian** based on land use regression models
Land use regression (LUR) models are mainly used for the simulation and prediction of conventional atmospheric pollutants. Whether the LUR models can...
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Stepwise integration of analytical hierarchy process with machine learning algorithms for landslide, gully erosion and flash flood susceptibility map** over the North-Moungo perimeter, Cameroon
BackgroundThe Cameroon Volcanic Line (CVL) is an oceanic-continental megastructure prone to geo-hazards, including landslide/mudslide, gully erosion...
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Investigating the impact of urban-environmental factors on air pollutants: a land use regression model approach and health risk assessment
The presence of pollutants in the earth's atmosphere has a direct impact on human health and the environment. So that pollutants such as carbon...
